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. 2021 Jun;33(6):063317.
doi: 10.1063/5.0053449. Epub 2021 Jun 24.

Effects of the filter microstructure and ambient air condition on the aerodynamic dispersion of sneezing droplets: A multiscale and multiphysics simulation study

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Effects of the filter microstructure and ambient air condition on the aerodynamic dispersion of sneezing droplets: A multiscale and multiphysics simulation study

Kyeongeun Lee et al. Phys Fluids (1994). 2021 Jun.

Abstract

Concerns have been ramping up with regard to the propagation of infectious droplets due to the recent COVID-19 pandemic. The effects of filter microstructures and ambient air flows on droplet dispersion by sneezing are investigated by a fully coupled Eulerian-Lagrangian computational modeling with a micro-to-macroscale bridging approach. Materials that are commonly applied to face masks are modeled to generate two different virtual masks with various levels of filtration efficiency, and the leakage percentages through the unsealed nose and cheek areas were set to 11% and 25%, respectively. The droplet propagation distance was simulated with and without mask wearing in still and windy conditions involving head wind, tail wind, and side wind. The results demonstrate that wearing a face mask reduces the transmittance distance of droplets by about 90%-95% depending on the mask type; nonetheless, the droplets can be transmitted to distances of 20-25 cm in the forward direction even with mask-wearing. Thus, a social distance of at least 20 cm between people would help to prevent them from becoming exposed to ejected droplets. This study is significant in that important aspects of mask materials, in this case the porous microstructure-dependent filtration efficiency and permeability under varied ambient flow conditions, were considered for the first time in an evaluation of the barrier performance against droplet transmittance through a multiphase computational fluid dynamics simulation of air-droplet interaction and turbulence flow dynamics.

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Figures

FIG. 1.
FIG. 1.
Schematic of research variables, including face mask materials, leakage rate depending on the characteristics in which they are worn, and environmental factors.
FIG. 2.
FIG. 2.
Multiscale modeling approach of the pore microstructure and the aerodynamics dispersion of respiratory droplets.
FIG. 3.
FIG. 3.
Modeling of face masks: (a) Type A mask with two layers of materials and (b) Type B mask with three layers of materials.
FIG. 4.
FIG. 4.
Sneezing droplets characteristics and particle penetration of virtual masks: (a) the size distribution of sneezing droplets referenced in previous studies and (b) fractional NaCl penetration of virtual masks for different particle sizes. Yellow round and green triangular dots are the actual particle penetration results of the corresponding particle size.
FIG. 5.
FIG. 5.
Velocity distribution and velocity streamline in filter media: (a) Type A and (b) Type B.
FIG. 6.
FIG. 6.
A person's body and a face mask generated via 3D scanning: (a) a person's upper body without (left) and with (right) a face mask; (b) flow leakages of 11% and 25% were set, respectively. Flow leakage only occurs through the periphery of the masks in the nose and cheek regions.
FIG. 7.
FIG. 7.
Sneezing droplet modeling: (a) flow velocity profile by sneezing, and (b) accumulated virtual droplet size distribution by sneezing.
FIG. 8.
FIG. 8.
Average leakage rates of face masks for 0.4 s: (a) average leakage rate of 11% for face mask Types A and B, and (b) average leakage rate of 25% for face mask Types A and B.
FIG. 9.
FIG. 9.
Boundary conditions: (a) Computational domain dimensions and boundary conditions for the indoor environment, and (b) computational grid without a face mask (c) wearing a face mask.
FIG. 10.
FIG. 10.
Transmitted distance of sneezing droplets over time without a face mask, simulated for Case 1: (a) side view, (b) enlarged side view and top view for droplet movement.
FIG. 11.
FIG. 11.
Distance transmitted to the front and side directions of droplets for different mask types with different leakage rates (abbreviated as LR): (a) in the front direction and (b) in the side direction.
FIG. 12.
FIG. 12.
Droplet trajectory profile of mask type A: (a) Case 2, (b) Case 3. “Mass Fraction of H2O” is the mass fraction of water vapor in air when the droplet evaporates, and a larger value means a higher mass of droplet evaporation.
FIG. 13.
FIG. 13.
Droplet trajectory profile of mask type B: (a) Case 4 and (b) Case 5.
FIG. 14.
FIG. 14.
Distance transmitted to the front and side directions of droplets in a windy environment: (a) in the front direction and (b) in the side direction (left to right).
FIG. 15.
FIG. 15.
Droplet behavior from 0 to 0.5 s: (a) isometric view in Case “6”–Case “8” and (b) side view in Case “6”–Case “7,” and top view in Case “8.”

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